Overcome the Limitation of Phenome-Wide Association Studies (PheWAS): Extension of PheWAS to Efficient and Robust Large-Scale ICD Codes Analysis.

The Phenome-wide association studies (PheWAS) have become widely used for efficient, high-throughput evaluation of relationship between a genetic factor and a large number of disease phenotypes, typically extracted from a DNA biobank linked with electronic medical records (EMR). Phecodes, billing code-derived disease case-control status, are usually used as outcome variables in PheWAS and logistic regression has been the standard choice of analysis method. Since the clinical diagnoses in EMR are often inaccurate with errors which can lead to biases in the odds ratio estimates, much effort has been put to accurately define the cases and controls to ensure an accurate analysis. Specifically in order to correctly classify controls in the population, an exclusion criteria list for each Phecode was manually compiled to obtain unbiased odds ratios. However, the accuracy of the list cannot be guaranteed without extensive data curation process. The costly curation process limits the efficiency of large-scale analyses that take full advantage of all structured phenotypic information available in EMR. Here, we proposed to estimate relative risks (RR) instead. We first demonstrated the desired nature of RR that overcomes the inaccuracy in the controls via theoretical formula. With simulation and real data application, we further confirmed that RR is unbiased without compiling exclusion criteria lists. With RR as estimates, we are able to efficiently extend PheWAS to a larger-scale, phenome construction agnostic analysis of phenotypes, using ICD 9/10 codes, which preserve much more disease-related clinical information than Phecodes.

Interoperability of phenome-wide multimorbidity patterns: a comparative study of two large-scale EHR systems.

Background: Electronic health records (EHR) are increasingly used for studying multimorbidities. However, concerns about accuracy, completeness, and EHRs being primarily designed for billing and administrative purposes raise questions about the consistency and reproducibility of EHR-based multimorbidity research. Methods: Utilizing phecodes to represent the disease phenome, we analyzed pairwise comorbidity strengths using a dual logistic regression approach and constructed multimorbidity as an undirected weighted graph. We assessed the consistency of the multimorbidity networks within and between two major EHR systems at local (nodes and edges), meso (neighboring patterns), and global (network statistics) scales. We present case studies to identify disease clusters and uncover clinically interpretable disease relationships. We provide an interactive web tool and a knowledge base combining data from multiple sources for online multimorbidity analysis. Findings: Analyzing data from 500,000 patients across Vanderbilt University Medical Center and Mass General Brigham health systems, we observed a strong correlation in disease frequencies (Kendall's τ = 0.643) and comorbidity strengths (Pearson ρ = 0.79). Consistent network statistics across EHRs suggest similar structures of multimorbidity networks at various scales. Comorbidity strengths and similarities of multimorbidity connection patterns align with the disease genetic correlations. Graph-theoretic analyses revealed a consistent core-periphery structure, implying efficient network clustering through threshold graph construction. Using hydronephrosis as a case study, we demonstrated the network's ability to uncover clinically relevant disease relationships and provide novel insights. Interpretation: Our findings demonstrate the robustness of large-scale EHR data for studying phenome-wide multimorbidities. The alignment of multimorbidity patterns with genetic data suggests the potential utility for uncovering shared biology of diseases. The consistent core-periphery structure offers analytical insights to discover complex disease interactions. This work also sets the stage for advanced disease modeling, with implications for precision medicine. Funding: VUMC Biostatistics Development Award, the National Institutes of Health, and the VA CSRD.

Repurposing N-acetylcysteine for management of non-acetaminophen induced acute liver failure: an evidence scan from a global health perspective.

Background: The World Health Organization (WHO)'s Essential Medicines List (EML) plays an important role in advocating for access to key treatments for conditions affecting people in all geographic settings. We applied our established drug repurposing methods to one EML agent, N-acetylcysteine (NAC), to identify additional uses of relevance to the global health community beyond its existing EML indication (acetaminophen toxicity). Methods: We undertook a phenome-wide association study (PheWAS) of a variant in the glutathione synthetase (GSS) gene in approximately 35,000 patients to explore novel indications for use of NAC, which targets glutathione. We then evaluated the evidence regarding biologic plausibility, efficacy, and safety of NAC use in the new phenotype candidates. Results: PheWAS of GSS variant R418Q revealed increased risk of several phenotypes related to non-acetaminophen induced acute liver failure (ALF), indicating that NAC may represent a therapeutic option for treating this condition. Evidence review identified practice guidelines, systematic reviews, clinical trials, retrospective cohorts and case series, and case reports. This evidence suggesting benefit of NAC use in this subset of ALF patients. The safety profile of NAC in this literature was also concordant with existing evidence on safety of this agent in acetaminophen-induced ALF. Conclusions: This body of literature indicates efficacy and safety of NAC in non-acetaminophen induced ALF. Given the presence of NAC on the EML, this medication is likely to be available across a range of resource settings; promulgating its use in this novel subset of ALF can provide healthcare professionals and patients with a valuable and safe complement to supportive care for this disease.

Taking AIM at serious illness: implementing an access to investigational medicines expanded access program.

When seriously ill patients have exhausted all treatment options available as part of usual care, the use of investigational agents may be warranted. Food and Drug Administration's (FDA) Expanded Access (EA) pathway provides a mechanism for these patient's physicians to pursue use of an investigational agent outside of a clinical trial when trial enrollment is not a feasible option. Though FDA has recently implemented processes to significantly streamline the regulatory portion of the process, the overall pathway has several time-consuming components including communication with the pharmaceutical company and the associated institutional requirements for EA use (contracting, Institutional Review Board [IRB], pharmacy, billing). Here, we present our experience building infrastructure at the Vanderbilt University Medical Center (VUMC) to support physicians and patients in pursuing EA, called the Access to Investigational Medicines (AIM) Platform, aligning the needs and responsibilities of institutional stakeholders and streamlining to ensure efficiency and regulatory compliance. Since its launch, the AIM team has experienced steady growth, supporting 40 EA cases for drugs/biologics, including both single patient cases and intermediate-size EA protocols in the emergent and non-emergent setting. As the EA pathway is a complex process that requires expert facilitation, we propose prioritizing EA support infrastructure at major academic medical centers as an essential regulatory knowledge function.

Using a multicultural and multilingual awareness-raising strategy to enhance enrollment of racially underrepresented minoritized communities - the PassITON trial.

Racially and ethnically minoritized populations have been historically excluded and underrepresented in research. This paper will describe best practices in multicultural and multilingual awareness-raising strategies used by the Recruitment Innovation Center to increase minoritized enrollment into clinical trials. The Passive Immunity Trial for Our Nation will be used as a primary example to highlight real-world application of these methods to raise awareness, engage community partners, and recruit diverse study participants.

Interactive network-based clustering and investigation of multimorbidity association matrices with associationSubgraphs.

MOTIVATION: Making sense of networked multivariate association patterns is vitally important to many areas of high-dimensional analysis. Unfortunately, as the data-space dimensions grow, the number of association pairs increases in O(n2); this means that traditional visualizations such as heatmaps quickly become too complicated to parse effectively. RESULTS: Here, we present associationSubgraphs: a new interactive visualization method to quickly and intuitively explore high-dimensional association datasets using network percolation and clustering. The goal is to provide an efficient investigation of association subgraphs, each containing a subset of variables with stronger and more frequent associations among themselves than the remaining variables outside the subset, by showing the entire clustering dynamics and providing subgraphs under all possible cutoff values at once. Particularly, we apply associationSubgraphs to a phenome-wide multimorbidity association matrix generated from an electronic health record and provide an online, interactive demonstration for exploring multimorbidity subgraphs. AVAILABILITY AND IMPLEMENTATION: An R package implementing both the algorithm and visualization components of associationSubgraphs is available at https://github.com/tbilab/associationsubgraphs. Online documentation is available at https://prod.tbilab.org/associationsubgraphs_info/. A demo using a multimorbidity association matrix is available at https://prod.tbilab.org/associationsubgraphs-example/.

Neutralizing COVID-19 Convalescent Plasma in Adults Hospitalized With COVID-19: A Blinded, Randomized, Placebo-Controlled Trial.

BACKGROUND: Convalescent plasma has been one of the most common treatments for COVID-19, but most clinical trial data to date have not supported its efficacy. RESEARCH QUESTION: Is rigorously selected COVID-19 convalescent plasma with neutralizing anti-SARS-CoV-2 antibodies an efficacious treatment for adults hospitalized with COVID-19? STUDY DESIGN AND METHODS: This was a multicenter, blinded, placebo-controlled randomized clinical trial among adults hospitalized with SARS-CoV-2 infection and acute respiratory symptoms for < 14 days. Enrolled patients were randomly assigned to receive one unit of COVID-19 convalescent plasma (n = 487) or placebo (n = 473). The primary outcome was clinical status (disease severity) 14 days following study infusion measured with a seven-category ordinal scale ranging from discharged from the hospital with resumption of normal activities (lowest score) to death (highest score). The primary outcome was analyzed with a multivariable ordinal regression model, with an adjusted odds ratio (aOR) < 1.0 indicating more favorable outcomes with convalescent plasma than with placebo. In secondary analyses, trial participants were stratified according to the presence of endogenous anti-SARS-CoV-2 antibodies ("serostatus") at randomization. The trial included 13 secondary efficacy outcomes, including 28-day mortality. RESULTS: Among 974 randomized patients, 960 were included in the primary analysis. Clinical status on the ordinal outcome scale at 14 days did not differ between the convalescent plasma and placebo groups in the overall population (aOR, 1.04; one-seventh support interval [1/7 SI], 0.82-1.33), in patients without endogenous antibodies (aOR, 1.15; 1/7 SI, 0.74-1.80), or in patients with endogenous antibodies (aOR, 0.96; 1/7 SI, 0.72-1.30). None of the 13 secondary efficacy outcomes were different between groups. At 28 days, 89 of 482 (18.5%) patients in the convalescent plasma group and 80 of 465 (17.2%) patients in the placebo group had died (aOR, 1.04; 1/7 SI, 0.69-1.58). INTERPRETATION: Among adults hospitalized with COVID-19, including those seronegative for anti-SARS-CoV-2 antibodies, treatment with convalescent plasma did not improve clinical outcomes. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov; No.: NCT04362176; URL: www. CLINICALTRIALS: gov.

Securely sharing DSMB reports to speed decision making from multiple, concurrent, independent studies of similar treatments in COVID-19.

Introduction: As clinical trials were rapidly initiated in response to the COVID-19 pandemic, Data and Safety Monitoring Boards (DSMBs) faced unique challenges overseeing trials of therapies never tested in a disease not yet characterized. Traditionally, individual DSMBs do not interact or have the benefit of seeing data from other accruing trials for an aggregated analysis to meaningfully interpret safety signals of similar therapeutics. In response, we developed a compliant DSMB Coordination (DSMBc) framework to allow the DSMB from one study investigating the use of SARS-CoV-2 convalescent plasma to treat COVID-19 to review data from similar ongoing studies for the purpose of safety monitoring. Methods: The DSMBc process included engagement of DSMB chairs and board members, execution of contractual agreements, secure data acquisition, generation of harmonized reports utilizing statistical graphics, and secure report sharing with DSMB members. Detailed process maps, a secure portal for managing DSMB reports, and templates for data sharing and confidentiality agreements were developed. Results: Four trials participated. Data from one trial were successfully harmonized with that of an ongoing trial. Harmonized reports allowing for visualization and drill down into the data were presented to the ongoing trial's DSMB. While DSMB deliberations are confidential, the Chair confirmed successful review of the harmonized report. Conclusion: It is feasible to coordinate DSMB reviews of multiple independent studies of a similar therapeutic in similar patient cohorts. The materials presented mitigate challenges to DSMBc and will help expand these initiatives so DSMBs may make more informed decisions with all available information.

Assessment of Awake Prone Positioning in Hospitalized Adults With COVID-19: A Nonrandomized Controlled Trial.

Importance: Awake prone positioning may improve hypoxemia among patients with COVID-19, but whether it is associated with improved clinical outcomes remains unknown. Objective: To determine whether the recommendation of awake prone positioning is associated with improved outcomes among patients with COVID-19-related hypoxemia who have not received mechanical ventilation. Design, Setting, and Participants: This pragmatic nonrandomized controlled trial was conducted at 2 academic medical centers (Vanderbilt University Medical Center and NorthShore University HealthSystem) during the COVID-19 pandemic. A total of 501 adult patients with COVID-19-associated hypoxemia who had not received mechanical ventilation were enrolled from May 13 to December 11, 2020. Interventions: Patients were assigned 1:1 to receive either the practitioner-recommended awake prone positioning intervention (intervention group) or usual care (usual care group). Main Outcomes and Measures: Primary outcome analyses were performed using a bayesian proportional odds model with covariate adjustment for clinical severity ranking based on the World Health Organization ordinal outcome scale, which was modified to highlight the worst level of hypoxemia on study day 5. Results: A total of 501 patients (mean [SD] age, 61.0 [15.3] years; 284 [56.7%] were male; and most [417 (83.2%)] were self-reported non-Hispanic or non-Latinx) were included. Baseline severity was comparable between the intervention vs usual care groups, with 170 patients (65.9%) vs 162 patients (66.7%) receiving oxygen via standard low-flow nasal cannula, 71 patients (27.5%) vs 62 patients (25.5%) receiving oxygen via high-flow nasal cannula, and 16 patients (6.2%) vs 19 patients (7.8%) receiving noninvasive positive-pressure ventilation. Nursing observations estimated that patients in the intervention group spent a median of 4.2 hours (IQR, 1.8-6.7 hours) in the prone position per day compared with 0 hours (IQR, 0-0.7 hours) per day in the usual care group. On study day 5, the bayesian posterior probability of the intervention group having worse outcomes than the usual care group on the modified World Health Organization ordinal outcome scale was 0.998 (posterior median adjusted odds ratio [aOR], 1.63; 95% credibility interval [CrI], 1.16-2.31). However, on study days 14 and 28, the posterior probabilities of harm were 0.874 (aOR, 1.29; 95% CrI, 0.84-1.99) and 0.673 (aOR, 1.12; 95% CrI, 0.67-1.86), respectively. Exploratory outcomes (progression to mechanical ventilation, length of stay, and 28-day mortality) did not differ between groups. Conclusions and Relevance: In this nonrandomized controlled trial, prone positioning offered no observed clinical benefit among patients with COVID-19-associated hypoxemia who had not received mechanical ventilation. Moreover, there was substantial evidence of worsened clinical outcomes at study day 5 among patients recommended to receive the awake prone positioning intervention, suggesting potential harm. Trial Registration: ClinicalTrials.gov Identifier: NCT04359797.

Standardized two-step testing of antibody activity in COVID-19 convalescent plasma.

The COVID-19 pandemic revealed an urgent need for rapid profiling of neutralizing antibody responses and development of antibody therapeutics. The current Food and Drug Administration-approved serological tests do not measure antibody-mediated viral neutralization, and there is a need for standardized quantitative neutralization assays. We report a high-throughput two-step profiling approach for identifying neutralizing convalescent plasma. Screening and downselection for serum antibody binding to the receptor-binding domain are followed by quantitative neutralization testing using a chimeric vesicular stomatitis virus expressing spike protein of SARS-CoV-2 in a real-time cell analysis assay. This approach enables a predictive screening process for identifying plasma units that neutralize SARS-CoV-2. To calibrate antibody neutralizing activity in serum from convalescent plasma donors, we introduce a neutralizing antibody standard reagent composed of two human antibodies that neutralize SARS-CoV strains, including SARS-CoV-2 variants of concern. Our results provide a framework for establishing a standardized assessment of antibody-based interventions against COVID-19.

The Recruitment Innovation Center: Developing novel, person-centered strategies for clinical trial recruitment and retention.

Clinical trials continue to face significant challenges in participant recruitment and retention. The Recruitment Innovation Center (RIC), part of the Trial Innovation Network (TIN), has been funded by the National Center for Advancing Translational Sciences of the National Institutes of Health to develop innovative strategies and technologies to enhance participant engagement in all stages of multicenter clinical trials. In collaboration with investigator teams and liaisons at Clinical and Translational Science Award institutions, the RIC is charged with the mission to design, field-test, and refine novel resources in the context of individual clinical trials. These innovations are disseminated via newsletters, publications, a virtual toolbox on the TIN website, and RIC-hosted collaboration webinars. The RIC has designed, implemented, and promised customized recruitment support for 173 studies across many diverse disease areas. This support has incorporated site feasibility assessments, community input sessions, recruitment materials recommendations, social media campaigns, and an array of study-specific suggestions. The RIC's goal is to evaluate the efficacy of these resources and provide access to all investigating teams, so that more trials can be completed on time, within budget, with diverse participation, and with enough accrual to power statistical analyses and make substantive contributions to the advancement of healthcare.

Human and Machine Intelligence Together Drive Drug Repurposing in Rare Diseases.

Repurposing is an increasingly attractive method within the field of drug development for its efficiency at identifying new therapeutic opportunities among approved drugs at greatly reduced cost and time of more traditional methods. Repurposing has generated significant interest in the realm of rare disease treatment as an innovative strategy for finding ways to manage these complex conditions. The selection of which agents should be tested in which conditions is currently informed by both human and machine discovery, yet the appropriate balance between these approaches, including the role of artificial intelligence (AI), remains a significant topic of discussion in drug discovery for rare diseases and other conditions. Our drug repurposing team at Vanderbilt University Medical Center synergizes machine learning techniques like phenome-wide association study-a powerful regression method for generating hypotheses about new indications for an approved drug-with the knowledge and creativity of scientific, legal, and clinical domain experts. While our computational approaches generate drug repurposing hits with a high probability of success in a clinical trial, human knowledge remains essential for the hypothesis creation, interpretation, "go-no go" decisions with which machines continue to struggle. Here, we reflect on our experience synergizing AI and human knowledge toward realizable patient outcomes, providing case studies from our portfolio that inform how we balance human knowledge and machine intelligence for drug repurposing in rare disease.

Passive Immunity Trial for Our Nation (PassITON): study protocol for a randomized placebo-control clinical trial evaluating COVID-19 convalescent plasma in hospitalized adults.

BACKGROUND: Convalescent plasma is being used widely as a treatment for coronavirus disease 2019 (COVID-19). However, the clinical efficacy of COVID-19 convalescent plasma is unclear. METHODS: The Passive Immunity Trial for Our Nation (PassITON) is a multicenter, placebo-controlled, blinded, randomized clinical trial being conducted in the USA to provide high-quality evidence on the efficacy of COVID-19 convalescent plasma as a treatment for adults hospitalized with symptomatic disease. Adults hospitalized with COVID-19 with respiratory symptoms for less than 14 days are eligible. Enrolled patients are randomized in a 1:1 ratio to 1 unit (200-399 mL) of COVID-19 convalescent plasma that has demonstrated neutralizing function using a SARS-CoV-2 chimeric virus neutralization assay. Study treatments are administered in a blinded fashion and patients are followed for 28 days. The primary outcome is clinical status 14 days after study treatment as measured on a 7-category ordinal scale assessing mortality, respiratory support, and return to normal activities of daily living. Key secondary outcomes include mortality and oxygen-free days. The trial is projected to enroll 1000 patients and is designed to detect an odds ratio ≤ 0.73 for the primary outcome. DISCUSSION: This trial will provide the most robust data available to date on the efficacy of COVID-19 convalescent plasma for the treatment of adults hospitalized with acute moderate to severe COVID-19. These data will be useful to guide the treatment of COVID-19 patients in the current pandemic and for informing decisions about whether developing a standardized infrastructure for collecting and disseminating convalescent plasma to prepare for future viral pandemics is indicated. TRIAL REGISTRATION: ClinicalTrials.gov NCT04362176 . Registered on 24 April 2020.

Passive Immunity Trial for Our Nation (PassITON): study protocol for a randomized placebo-control clinical trial evaluating COVID-19 convalescent plasma in hospitalized adults.

Background: Convalescent plasma is being used widely as a treatment for coronavirus disease 2019 (COVID-19). However, the clinical efficacy of COVID-19 convalescent plasma is unclear. Methods: The Pass ive I mmunity T rial for O ur N ation (PassITON), is a multicenter, placebo-controlled, blinded, randomized clinical trial being conducted in the United States to provide high-quality evidence on the efficacy of COVID-19 convalescent plasma as a treatment for adults hospitalized with symptomatic disease. Adults hospitalized with COVID-19 with respiratory symptoms for less than 14 days are eligible. Enrolled patients are randomized in a 1:1 ratio to 1 unit (200-399 mL) of COVID-19 convalescent plasma that has demonstrated neutralizing function using a SARS-CoV-2 chimeric virus neutralization assay. Study treatments are administered in a blinded fashion and patients are followed for 28 days. The primary outcome is clinical status 14 days after study treatment as measured on a 7-category ordinal scale assessing mortality, respiratory support, and return to normal activities of daily living. Key secondary outcomes include mortality and oxygen-free days. The trial is projected to enroll 1000 patients and is designed to detect an odds ratio ≤ 0.73 for the primary outcome. Discussion: This trial will provide the most robust data available to date on the efficacy of COVID-19 convalescent plasma for the treatment of adults hospitalized with acute moderate to severe COVID-19. These data will be useful to guide the treatment of COVID-19 patients in the current pandemic and for informing decisions about whether developing a standardized infrastructure for collecting and disseminating convalescent plasma to prepare for future viral pandemics is indicated. Trial Registration: ClinicalTrials.gov: NCT04362176. Date of trial registration: April 24, 2020, https://clinicaltrials.gov/ct2/show/NCT04362176.

A high-throughput liquid bead array assay confirms strong correlation between SARS-CoV-2 antibody level and COVID-19 severity.

A detailed understanding of the adaptive host response to SARS-CoV-2 infection in humans is urgently needed. We developed a sensitive, high-throughput, and efficient assay using liquid bead array technology. We observed advantages over traditional ELISA for the detection and quantification of binding IgG against the receptor binding domain (RBD) of SARS-CoV-2. To determine whether COVID-19 symptom severity correlates with SARS-CoV-2 IgG, we measured anti-RBD IgG levels from 67 subjects recovered from PCR-confirmed COVID-19. We found that COVID-19 symptom severity strongly correlated with RBD IgG level (p < 0.001). These findings have substantial implications for public policy surrounding assessments of antibody responses and possible immunity, as not all cases of COVID-19 can be assumed to generate a protective antibody response, and mild disease in particular is capable of generating very low-level anti-RBD IgG levels. These findings also have important implications for the selection of donors for convalescent plasma to be used therapeutically.

Learning From What We Do, and Doing What We Learn: A Learning Health Care System in Action.

Different models of learning health systems are emerging. At Vanderbilt University Medical Center, the Learning Health Care System (LHS) Platform was established with the goal of creating generalizable knowledge. This differentiates the LHS Platform from other efforts that have adopted a quality improvement paradigm. By supporting pragmatic trials at the intersection of research, operations, and clinical care, the LHS Platform was designed to yield evidence for advancing content and processes of care through carefully designed, rigorous study. The LHS Platform provides the necessary infrastructure and governance to leverage translational, transdisciplinary team science to inform clinical and operational decision making across the health system. The process transforms a clinical or operational question into a research question amenable to a pragmatic trial. Scientific, technical, procedural, and human infrastructure is maintained for the design and execution of individual LHS projects. This includes experienced pragmatic trialists, project management, data science inclusive of biostatistics and clinical informatics, and regulatory support. Careful attention is paid to stakeholder engagement, including health care providers and the community. Capturing lessons from each new study, the LHS Platform continues to mature with plans to integrate implementation science and to complement clinical and process outcomes with cost and value considerations. The Vanderbilt University Medical Center LHS Platform is now a pillar of the health care system and leads the evolving culture of learning from what we do and doing what we learn.

The Astounding Breadth of Health Disparity: Phenome-Wide Effects of Race on Disease Risk.

OBJECTIVE: We conducted a phenotype-wide association study (PheWAS) to compare diagnoses among Blacks with those of Whites in one health center in Tennessee using data from 1,883,369 patients. METHODS: We used our deidentified EHR, the Synthetic Derivative, to assess risk of diagnoses associated with Black as compared with White race using Firth logistic regression with covariates including age, sex, and density of clinical encounters. RESULTS: There were anchoring associations in both directions, including the highest increased risk for Blacks of having sickle cell anemia, and strongest decreased risk of basal cell carcinoma. Results included established areas of disparity and many novel associations. CONCLUSIONS: PheWAS is a viable tool for calculating risk associated with any biomarker. The current analysis provide a new approach to generating hypotheses and understanding the breadth of health disparities. Future analyses will further explore causality, risk factors, and potential confounders not accounted for here.

PheWAS-ME: a web-app for interactive exploration of multimorbidity patterns in PheWAS.

SUMMARY: Electronic health records (EHRs) linked with a DNA biobank provide unprecedented opportunities for biomedical research in precision medicine. The Phenome-wide association study (PheWAS) is a widely used technique for the evaluation of relationships between genetic variants and a large collection of clinical phenotypes recorded in EHRs. PheWAS analyses are typically presented as static tables and charts of summary statistics obtained from statistical tests of association between a genetic variant and individual phenotypes. Comorbidities are common and typically lead to complex, multivariate gene-disease association signals that are challenging to interpret. Discovering and interrogating multimorbidity patterns and their influence in PheWAS is difficult and time-consuming. We present PheWAS-ME: an interactive dashboard to visualize individual-level genotype and phenotype data side-by-side with PheWAS analysis results, allowing researchers to explore multimorbidity patterns and their associations with a genetic variant of interest. We expect this application to enrich PheWAS analyses by illuminating clinical multimorbidity patterns present in the data. AVAILABILITY AND IMPLEMENTATION: A demo PheWAS-ME application is publicly available at https://prod.tbilab.org/phewas_me/. Sample datasets are provided for exploration with the option to upload custom PheWAS results and corresponding individual-level data. Online versions of the appendices are available at https://prod.tbilab.org/phewas_me_info/. The source code is available as an R package on GitHub (https://github.com/tbilab/multimorbidity_explorer). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Uncovering Outcome Disparities of ß2 Adrenergic Agonists in Blacks: A Systematic Review.

PURPOSE: Outcome differences driven by variation in Blacks' biologic response to treatment may contribute to persistent racial disparities in asthma morbidity and mortality. This review assessed systematic variation in ß2 agonist treatment outcomes among Blacks compared to other groups. METHODS: We conducted a systematic review of studies reporting differential response to ß2 agonists among Blacks, including studies identifying pharmacogenetic variants. RESULTS: Of 3158 papers, 20 compared safety or efficacy of ß2 agonists among Blacks as compared with other subgroups. Six papers evaluating efficacy of short-acting ß2 agonists (SABA) found similar or improved results among Blacks compared with other groups, while one small study found reduced response to SABA therapy among Blacks. Reports of safety and efficacy of long-acting ß2 agonists (LABA) indicated similar results among Blacks in four papers, while four reports found reduced safety among Blacks, as compared with other groups. Four papers assessed genomic variation and relative treatment response in Blacks, with two finding significant effects of the p.Arg16Gly variant in ADRB2 on ß2 agonist response and one finding significant gene-gene IL6/IL6R interaction effects on albuterol response. CONCLUSIONS: Evidence suggests the potential for differences in ß2 agonist outcomes among Blacks compared with other groups. This literature, however, remains small and significantly underpowered for substantive conclusions. There are notable opportunities for adequately-powered investigations exploring safety and efficacy of ß2 agonists among Blacks, including pharmacogenomic modifiers of response.